Woldag, H.; Waldmann, G.; Knösche, T. R.; Maess, B.; Friederici, A. D.; Hummelsheim, H.: Rapidly induced changes in neuromagnetic fields following repetitive hand movements. European Journal of Neurology 13 (7), S. 723 - 728 (2006)

Wolters, C. H.; Anwander, A.; Tricoche, X.; Weinstein, D.; Koch, M. A.; MacLeod, R. S.: Influence of tissue conductivity anisotropy on EEG/MEG field and return current computation in a realistic head model: A simulation and visualization study using high-resolution finite element modeling. NeuroImage 30 (3), S. 813 - 826 (2006)

Brass, M.; Ullsperger, M.; Knösche, T. R.; von Cramon, D. Y.; Phillips, N. A.: Who comes first? The role of the prefrontal and parietal cortex in cognitive control. Journal of Cognitive Neuroscience 17 (9), S. 1367 - 1375 (2005)

Güllmar, D.; Reichenbach, J. R.; Anwander, A.; Knösche, T. R.; Wolters, C. H.; Eiselt, M.; Haueisen, J.: Influence of anisotropic conductivity of the white matter tissue on EEG source reconstruction a FEM simulation study. International Journal of Bioelectromagnetism 7 (1), S. 108 - 110 (2005)

Knösche, T. R.; Neuhaus, C.; Haueisen, J.; Alter, K.; Maess, B.; Witte, O. W.; Friederici, A. D.: Perception of phrase structure in music. Human Brain Mapping 24 (4), S. 259 - 273 (2005)

Wolters, C. H.; Anwander, A.; Tricoche, X.; Lew, S.; Johnson, C. R.: Influence of local and remote white matter conductivity anisotropy for a thalamic source on EEG/MEG field and return current computation. International Journal of Bioelectromagnetism 7 (1), S. 203 - 206 (2005)

Wolters, C. H.; Grasedyck, L.; Anwander, A.; Hackbush, W.: Efficient computation of lead field bases and influence matrix for the FEM-based EEG and MEG inverse problem. Inverse Problems 20 (4), S. 1099 - 1116 (2004)

Herrmann, C. S.; Lenz, D.; Junge, S.; Busch, N. A.; Maess, B.: Memory-matches evoke human gamma-responses. BMC Neuroscience 5, 13 (2004)

Nakamura, A.; Maess, B.; Knösche, T. R.; Gunter, T. C.; Bach, P.; Friederici, A. D.: Cooperation of different neuronal systems during hand sign recognition. NeuroImage 23, S. 25 - 34 (2004)

Zanow, F.; Knösche, T. R.: ASA-Advanced Source Analysis of Continuous and Event-Related EEG/MEG Signals. Brain Topography 16 (4), S. 287 - 290 (2004)

Knösche, T. R.; Haueisen, J.: EEG/MEG source reconstruction: Textbook for electro-and magnetoencephalography. Springer, Cham (2022), XIX, 417 S.

Brauer, H.; Ziolkowski, M.; Weise, K.; Carlstedt, M.; Uhlig, R. P.; Zec, M.: Motion-induced eddy current techniques for non-destructive testing and evaluation. IET Press, UK (2019), 360 S.

Haueisen, J.; Knösche, T. R.: Forward modeling and tissue conductivities. In: Magnetoencephalography: From signals to dynamic cortical networks, S. 145 - 165 (Hg. Supek, S.). Springer, Cham (2019)

Codecasa, L.; Weise, K.; Di Rienzo, L.; Haueisen, J.: MOR-based uncertainty quantification in transcranial magnetic stimulation. In: Model reduction of parametrized systems (Hg. Benner, P.; Ohlberger, M.; Patera, A.; Rozza, G.; Urban, K.). Springer, Cham (2017)

Knösche, T. R.: Chaos, neural population models and. In: Encyclopedia of computational neuroscience, S. 599 - 601 (Hg. Jaeger, D.; Jung, R.). Springer, New York (2015)

Knösche, T. R.: Bifurcations, neural population models and. In: Encyclopedia of computational neuroscience, S. 380 - 383 (Hg. Jaeger, D.; Jung, R.). Springer, New York (2015)

Knösche, T. R.: Jansen-Rit model. In: Encyclopedia of computational neuroscience, S. 1463 - 1466 (Hg. Jaeger, D.; Jung, R.). Springer, New York (2015)

Haueisen, J.; Knösche, T. R.: Forward modeling and tissue conductivities. In: Magnetoencephalography, S. 107 - 127 (Hg. Supek , S.; Aine, C. J.). Springer, Berlin (2014)

Wiebel, A.; Müller, C.; Garth, C.; Knösche, T. R.: A system for combined visualization of EEG and diffusion tensor imaging tractography data. In: Visualization and processing of tensors and higher order descriptors for multi-valued data, S. 325 - 337. Springer (2014)

Hlawitschka, M.; Weber, G. H.; Anwander, A.; Carmichael, O. T.; Hamann, B.; Scheuermann, G.: Interactive volume rendering of diffusion tensor data. In: Visualization and processing of tensor fields: Advances and perspectives, S. 161 - 176 (Hg. Laidlaw, D. H.; Weickert, J.). Springer, Berlin (2009)